Deep Learning-Based Brain Tumour Detection Using Robust Active Shape Model Algorithm ... This suggests that the flammability classification of the whole tumour, tumour core, and proliferative tumor ...

The research work carried out uses Deep learning models like convolutional neural network (CNN) model and VGG-16 architecture (built from scratch) to detect the tumor region in the scanned brain ...

Diffusion MRI and machine learning models classify childhood brain tumours. The CNN demonstrated good generalization capability, scoring an accuracy of 91.95% on the external test data. The results ...

Hyderabad - KL Deemed to be University has conferred a Doctorate degree on Ms. A. Vinisha, a research scholar from the Department of Electronics and Communication Engineering (ECE) at KLH, Aziznagar ...

In summary, by augmenting the dataset and training a VGG16 model, we were able to develop a highly accurate brain tumor detection system. This system has the potential to aid healthcare professionals ...

Summary: AI models trained on MRI data can now distinguish brain tumors from healthy tissue with high accuracy, nearing human performance.Using convolutional neural networks and transfer learning from ...

Deep learning characterization of brain tumours with diffusion weighted imaging. Journal of Theoretical Biology , 2023; 557: 111342 DOI: 10.1016/j.jtbi.2022.111342 Cite This Page : ...

Please use one of the following formats to cite this article in your essay, paper or report: APA. Cuffari, Benedette. (2025, April 07). Using Deep Learning for Brain Imaging Data Analysis.